Raphael Townshend News Today

Atomic AI, a biotechnology company fusing cutting-edge machine learning with state-of-the-art structural biology to unlock RNA drug discovery, announced that the Company has created the first large language model (LLM) leveraging chemical mapping data. In a preprint paper published on bioRxiv, Atomic AI describes ...

SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)--Dec 15, 2023--

FinSMEs is the financial news site dedicated to covering venture capital, private equity, and merger and acquisition deals in real time!

The biotech industry is experiencing a rush of AI-powered tools for many aspects of the complex drug discovery process. But one that has flown under the radar,

With $35M in new funding, Atomic AI aims to do for RNA what AlphaFold did for proteins, and find entirely new treatments in the process.

AI-based drug discovery platform Atomic AI, senior lifestyle company Mighty Health, Lithuania-based Oxipit and cybersecurity firm MedCrypt also closed funding rounds.

Out of the six-hundred honorees nominated among twenty categories, sixty-two have studied or researched at Stanford.

Stanford researchers develop machine learning methods that accurately predict the 3D shapes of drug targets and other important biological molecules, even when only limited data is available.

Researchers present ARES (Atomic Rotationally Equivariant Scorer) – a machine learning method that significantly improves the computational prediction of RNA structures over previous approaches. Like proteins, RNA molecules twist and fold into intricate three-dimensional shapes that are crucial to their function.

Determining the 3D shapes of biological molecules is one of the hardest problems in modern biology and medical discovery. Companies and research institutions often spend millions of dollars to determine a molecular structure – and even such massive efforts are frequently unsuccessful.